§1.1 Field of the Invention
The present invention concerns advertising. In particular, the present invention concerns estimating cost and/or performance information for a candidate ad, and using such estimates to help advertisers.
§1.2 Background Information
Advertising using traditional media, such as television, radio, newspapers and magazines, is well known. Unfortunately, even when armed with demographic studies and entirely reasonable assumptions about the typical audience of various media outlets, advertisers recognize that much of their ad budget is simply wasted. Moreover, it is very difficult to identify and eliminate such waste.
Recently, advertising over more interactive media has become popular. For example, as the number of people using the Internet has exploded, advertisers have come to appreciate media and services offered over the Internet as a potentially powerful way to advertise.
Advertisers have developed several strategies in an attempt to maximize the value of such advertising. In one strategy, advertisers use popular presences or means for providing interactive media or services (referred to as “Web sites” in the specification without loss of generality) as conduits to reach a large audience. Using this first approach, an advertiser may place ads on the home page of the New York Times Web site, or the USA Today Web site, for example. In another strategy, an advertiser may attempt to target its ads to narrower niche audiences, thereby increasing the likelihood of a positive response by the audience. For example, an agency promoting tourism in the Costa Rican rainforest might place ads on the ecotourism-travel subdirectory of the Yahoo Web site.
Regardless of the strategy, Web site-based ads (also referred to as “Web ads”) are typically presented to their advertising audience in the form “banner ads”—i.e., a rectangular box that includes graphic components. When a member of the advertising audience (referred to as a “viewer” or “user” in the Specification without loss of generality) selects one of these banner ads by clicking on it, embedded hypertext links typically direct the viewer to the advertiser's Website. This process, wherein the viewer selects an ad, is commonly referred to as a “click-through” (“Click-through” is intended to cover any user selection.). The ratio of the number of click-throughs to the number of impressions of the ad (i.e., the number of times an ad is displayed) is commonly referred to as the “click-through rate” of the ad.
A “conversion” is said to occur when a user consummates a transaction related to a previously served ad. What constitutes a conversion may vary from case to case and can be determined in a variety of ways. For example, it may be the case that a conversion occurs when a user clicks on an ad, is referred to the advertiser's Web page, and consummates a purchase there before leaving that Web page. Alternatively, a conversion may be defined as a user being shown an ad, and making a purchase on the advertiser's Web page within a predetermined time (e.g., seven days). In yet another alternative, a conversion may be defined by an advertiser to be any measurable/observable user action such as, for example, downloading a white paper, navigating to at least a given depth of a Website, viewing at least a certain number of Web pages, spending at least a predetermined amount of time on a Website or Web page, registering with a Website, etc. Often, if user actions don't indicate a consummated purchase, they may indicate a sales lead, although user actions constituting a conversion are not limited to this. Indeed, many other definitions of what constitutes a conversion are possible. The ratio of the number of conversions to the number of impressions of the ad (i.e., the number of times an ad is displayed) is commonly referred to as the conversion rate. If a conversion is defined to be able to occur within a predetermined time after the serving of an ad, one possible definition of the conversion rate might only consider ads that have been served more than the predetermined time in the past.
Despite the initial promise of Website-based advertisement, there remain several problems with existing approaches. Although advertisers are able to reach a large audience, they are frequently dissatisfied with the return on their advertisement investment. Targeted ad serving has been used to increase the relevance, and consequently, the performance of online advertising. For example, search engines, such as Google, have enabled advertisers to target their ads so that they will be rendered with a search results page and so that they will be relevant, presumably, to the query that prompted the search results page. Other targeted advertising systems, such as those that target ads using e-mail information (See, e.g., the systems described in U.S. patent application Ser. No. 10/452,830 (incorporated herein by reference), titled “SERVING ADVERTISEMENTS USING INFORMATION ASSOCIATED WITH E-MAIL,” filed on Jun. 2, 2003 and listing Jeffrey A. Dean, Georges R. Hark and Paul Bucheit as inventors.), or those that target ads using document content (See, e.g., U.S. patent application Ser. No. 10/375,900 (incorporated herein by reference), titled “SERVING ADVERTISEMENTS BASED ON CONTENT,” filed on Feb. 26, 2003 and listing Darrell Anderson, Paul Bucheit, Alex Carobus, Claire Cui, Jeffrey A. Dean, Georges R. Hark, Deepak Jindal, and Narayanan Shivakumar as inventors.) may have similar challenges. That is, advertising systems would like to present advertisements that are relevant to the user requested information in general, and related to the current user interest in particular.
Such ad serving systems may serve ads in two steps. First, they may determine which ads are relevant to a given document request, search query, user, user location, etc. That is, they may determine which ads are eligible for serving. They may then score eligible ads using one or more factors such as the degree of relevance, offers (e.g., in terms of price offers, maximum price offers, etc.) made by the advertisers, ad performance, advertiser performance, user information, etc.
Generally, advertisers would like to know how their online advertising is performing, or how a hypothetical ad would likely perform. In fact, advertisers would like to be able to predict cost and/or performance information for one or more actual or hypothetical ads.